1. Field
The following description relates to an image processing method and apparatus.
2. Description of Related Art
In a field of gaze estimation technology, analyzing eye movement information varying in response to a change in a gaze may be a significant issue. Typically, there may be at least two general gaze tracking approaches, a geometric-based approach where specific features, e.g., corneal/retinal glints, are used to extract a gaze direction, and an appearance-based approach that may exploit many eye features together, or an entirety of a captured eye, to learn a mapping between eye appearance and gaze direction. In addition, compared to the explicit geometric features determined in geometric-based approaches, appearance-based approaches may treat an image as points in a high-dimensional space, such as a 20 pixel by 40 pixel intensity image being considered an 800-component vector, or a point in an 800-dimensional space. In the appearance-based approach there may further be a desire to derive a way to compare eye mappings without too much information, e.g., without too great of a capturing pixel resolution.
Thus, when eye movement information is being analyzed based on the change in the gaze, unnecessary information may be removed from an eye image, which may result in greater efficiency and accuracy of gaze applications based on image information and enhanced image alignment. However, with the extent of information in different and varying eye details, such as eye lids and eye lashes, there may typically be a need for sufficiently high resolution to capture such information, the analysis of which reduces efficiency of gaze applications.
In addition, in the example appearance-based approach, to accurately analyze the eye movement information, alignment of the eye image may be desirable. By detecting an eye of a user in the eye image at a high accuracy, a plurality of eye images may be aligned based on a predetermined reference.